Stroke Mortality Rates Vary in Local Communities in a Metropolitan Area

Introduction

Although the stroke mortality rate in the United States has been declining since the 1970s, stroke continues to be one of the leading causes of preventable death in this country.^1,2 Stroke is currently the 4th leading cause of death in the United States, accounting for roughly 1 out of every 19 deaths in 2009³ and costing an estimated $38.6 billion in direct healthcare expenditures and loss of productivity.⁴

Controlling risk factors like blood pressure, cholesterol, and glucose have been shown to decrease an individual’s risk of having a stroke.⁵ However, the aging of the population, coupled with the increasing prevalence of hypertension and diabetes mellitus, has led to predictions that there will be a nearly 22% increase in stroke prevalence in 2030 compared with 2010.⁴

Important differences exist in terms of which populations are more affected by stroke. For example, stroke mortality has been found to vary by socioeconomic status,^6,7 age,⁸ sex,¹ and race/ethnicity.^1,9,10 In 2009, the average age-adjusted stroke mortality rate (AASMR) for the United States was 38.9 per 100 000 population. Non-Hispanic blacks had by far the highest rates (55.7), followed by non-Hispanic whites (37.8), and then Hispanics (29.5).³

Although national- and city-level data are important and can be used to shape policy and inform the public about the current state of this epidemic, local-level data also play an instrumental role in this process. In a diverse yet segregated city like Chicago, averages mask disparities that can only be uncovered by examining data at the community or neighborhood level. Once those disparities are identified, targeting efforts to prevent stroke based on each community’s specific risk factors is a strategy that may help to reduce health disparities within the city.¹¹ To that end, in this article, we provide AASMRs for the city of Chicago and its 77 officially designated community areas, as well as by race/ethnicity. Given the large Hispanic population in Chicago, we are able to move beyond the broad categorization of Hispanic and provide data on Mexicans and Puerto Ricans as well. Data at this level are not readily available to the public but are imperative for designing and implementing effective health interventions.

Methods

Setting

Chicago is the third largest city in the United States, with 2 700 000 residents. The racial/ethnic makeup of Chicago in 2010 was 29% Hispanic, 32% non-Hispanic black, and 32% non-Hispanic white. In 2008, there were just under 20 000 deaths in the city.¹² Chicago is divided into 77 officially designated community areas, which are the sums of census tracts and have historically been used to examine local variations in health data.

Measures

We analyzed death certificates from Illinois Vital Records supplied to us by the Chicago Department of Public Health¹² for all deaths to residents of the city of Chicago during the years 2006, 2007, and 2008 (2008 being the most recent year for which data were available). We used data from these years to calculate a 3-year average AASMR. These certificates also contain data on the decedent’s community area of residence at the time of death.

Deaths from stroke were defined to consist of all deaths with an underlying cause coded as I60-I69 under the International Classification of Diseases, 10th Revision. Data for denominators were drawn from the US Census Bureau, 2000 and 2010. Using data from these 2 points, we performed linear interpolation to obtain the denominators for 2006, 2007, and 2008. All mortality rates were age adjusted to the US standard 2000 population.

Two demographic variables were included in the analysis: racial/ethnic makeup and median annual household income of each community area of residence. Data on the race/ethnic-specific populations in each community area were obtained from the US Census Bureau, 2000 and 2010. Linear interpolation was used to calculate the 2006 to 2008 3-year average percentages for each race/ethnic group. Our analysis includes multiple racial/ethnic groups within the city of Chicago: non-Hispanic white (white), non-Hispanic black (black), Hispanic, and the Hispanic subgroups Mexican and Puerto Rican. Data on median household income for each community area were obtained from the American Community Survey, 2010 (5-year estimates for 2006–2010).

For purposes of comparison, we present 3-year average AASMRs at the national level as well. We abstracted numerator data for 2006, 2007, and 2008 from death files obtained from the National Center for Health Statistics¹³ and used population data from the annual reports to calculate race/ethnic-specific 3-year averages for the United States.^14–16

Statistical Analysis

Data were analyzed using SAS version 9.2.¹⁷ We calculated the AASMRs for each of the 77 community areas and then correlated these with the race/ethnicity and the median household income of the area. Spearman correlation coefficients were calculated using the SAS procedure PROC CORR. t Tests were used to determine whether the correlation coefficients were statistically significant. Z scores were calculated to test whether the Chicago–US differences in AASMRs were significant and to test whether differences between racial/ethnic groups within Chicago were significant.³ A P value of 0.05 or less was considered statistically significant for all analyses.

Results

Table 1 displays the AASMRs for Chicago and the United States, in total and by race and ethnicity for the years 2006 to 2008 (3-year averages). The AASMR for Chicago was 44.9 per 100 000 population, significantly higher than the national rate of 42.2 (P<0.001). Nationally, as well as in Chicago, the highest AASMRs were found among blacks (60.9 and 57.0, respectively), whose rates were significantly higher than their white and Hispanic, including Mexican and Puerto Rican, counterparts in Chicago (37.8, 32.1, 30.4, and 40.1, respectively).

To gain further insight into these race/ethnic differences in AASMRs, we also calculated these rates at the community area level. Table 2 displays AASMRs, ranked from highest to lowest, along with the racial/ethnic makeup and annual household income for each of the 77 community areas in Chicago. The Figure displays a map of these community areas with light to dark shading for lowest to highest AASMRs. The AASMR ranged from a low of 23.2 to a high of 124.0. The community areas with the highest AASMRS (those in the 4th quartile) were overwhelmingly located on the west and south sides of the city and had predominantly black populations.

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Table 3 displays correlation coefficients for AASMRs and racial/ethnic makeup of a community area. There was a strong, positive correlation between the proportion of black residents in a community area and the AASMR (0.58; P<0.0001). Conversely, there was a strong, negative relationship between the proportion white and the AASMR (−0.61; P<0.0001). The correlation was negative and smaller but statistically significant for Hispanic people (−0.40; P<0.001).

Table 3 also displays correlation coefficients for AASMRs and median household income. Here, we observed a strong, negative relationship between household income and the AASMR for the entire city (−0.56; P<0.0001). This relationship prevailed for the 28 community areas that were predominantly (60% or more) black (−0.47; P=0.012). For the other areas, the relationship was weak and not statistically significant.

Discussion

This analysis explores disparities in AASMRs across several race/ethnic groups in the United States and Chicago. First, Chicago’s rate (44.9) is significantly higher than the national rate (42.2), despite the fact that blacks, whites, and Hispanics in Chicago fare better than their counterparts nationally. Indeed, among all the race/ethnic groups examined, Puerto Ricans were the only group to display higher stroke mortality rates in Chicago than at the national level. For both Chicago and the United States, above-average rates are found among blacks, whereas below-average rates are observed among whites, Puerto Ricans, and Mexicans (Table 1).

We observed substantial variation in stroke mortality rates across Chicago’s 77 community areas (Table 2). The community area–specific stroke mortality rates were highly correlated with the race/ethnic makeup of the community and its income (Table 3).

It is alarming how disproportionately blacks are affected by stroke. Of the 10 Chicago community areas with the highest stroke mortality rates, 9 are comprised of a population that is 83% or more black and the 10th is 86% Hispanic. Income disparities likely contribute to the higher stroke mortality rates among blacks.^18,19 Notably, the protective effect of income on stroke mortality was not observed in predominantly white or Hispanic community areas, suggesting that stroke mortality rates remain comparably lower for these groups regardless of income. It is worth noting that the lowest median household income in black communities was much lower than the minimum for Hispanic or white communities, implying there may be a threshold effect for income above which there is less impact of income on mortality. Alternatively, the lack of a significant relationship between income and stroke mortality in white and Hispanic communities may be due to the fact that the range of median household incomes among these communities is not as wide as it is across the black communities, making the correlation more difficult to identify.

In Chicago, Hispanics, and more specifically Mexicans, displayed the lowest stroke mortality rates among the groups examined in this analysis. Several theories have been proposed to explain this so-called Hispanic Paradox—the notion that, despite exhibiting a socioeconomic profile similar to that of blacks, Hispanics tend to experience better health outcomes than their black counterparts and indeed often outperform even whites. Stroke mortality among Mexicans in Chicago is certainly an example of this phenomenon, suggesting that this might be more aptly named the Mexican Paradox.

Early explanations of this apparent paradox, which included the healthy migrant effect^20,21 and the salmon bias,^20,22 have been challenged by alternative explanations like the barrio advantage, which posits that Mexican Americans living in predominantly Mexican neighborhoods have some protective cultural advantage that outweighs the disadvantages of poverty²³ and theories of how acculturation affects the immigrant population.^24–29 To the extent that Mexicans living in Chicago are more recent immigrants,³⁰ the lower rates of stroke mortality among this group might be partially attributable to a healthier lifestyle.

There is likely no single or simple explanation as to why certain community areas display elevated rates of stroke mortality. Rather, it may be a combination of varying factors. Some of these factors, like age, sex, and race/ethnicity cannot be controlled, whereas others like diabetes mellitus, hypertension, and high cholesterol can be prevented or managed, thereby reducing one’s risk of stroke. Unfortunately, the prevention/management of many of the risk factors for stroke can be a challenge for those living in racially segregated cities as racial residential segregation has been found to be associated with several chronic stressors and these chronic stressors are in turn associated with many risk factors for stroke.³¹

In addition to being disproportionately burdened with stroke risk factors, blacks (29.5%) are less likely than whites (41.3%) to be able to identify the warning signs of a stroke³²—an inability that leads to delays in getting to a hospital and getting time-sensitive treatment that can help to reduce stroke mortality and morbidity.³² Furthermore, for those who survive a stroke, residence in an economically disadvantaged community may be detrimental to their chances for long-term survival.³³

It is imperative that disparities in stroke mortality be addressed—both in Chicago and in similar large, diverse cities. Increased access to healthy food options and safe places for residents to exercise can decrease risk factors like obesity, hypertension, and diabetes mellitus. A public health campaign engaged in by these specific communities and led by local religious and political leaders could help raise awareness about the warning signs of a stroke, which would be integral to promoting early treatment and thus reducing poststroke morbidity.

Like many health disparities present among US populations, the racial disparities in stroke mortality rates in Chicago are largely attributable to what Phelan et al³⁴ have deemed the fundamental social causes of health inequalities. Among other things, the authors advocate for a redistribution of resources as one mechanism for reducing health disparities and we agree entirely. Although redistributing resources is an integral part of the long-term approach, we also see the development and implementation of health interventions as something that can be enacted more immediately.¹¹ In our view, one imperative step in the process of implementing a health intervention is to understand how the needs of each community differ and which communities are most in need. A local-level analysis like the one presented here facilitates just that and enables health officials to target communities with the highest mortality rates.

Methodological Considerations

In this analysis, we did not break stroke deaths out by type (ie, ischemic and hemorrhagic), which might provide interesting insight into the racial disparities in stroke mortality and we consider this an important direction for future research.

Conclusions

This study found that stroke mortality rates vary widely across community areas within Chicago and higher stroke mortality rates were observed in community areas with larger proportions of black residents and lower median household incomes. Racial disparities in stroke mortality were prevalent with the highest mortality rates observed among blacks.

Given the substantial variation in stroke mortality observed within Chicago, it is reasonable to assume that similar variation exists in other large metropolitan areas in the United States. Data like those presented in this analysis are imperative to developing targeted interventions and engaging the community, thus improving health and decreasing health disparities. We, therefore, encourage anyone working toward these or similar goals to consider the use of such an analysis.

Footnotes